Weakening memories by half-remembering them

fMRI and multi-voxel pattern analysis (MVPA)

I was heavily involved in efforts to analyze fMRI neuroimaging data multivariately. The basic idea is that we should be able to use machine learning tools to learn how the patterns in your brain activity indicate what you’re thinking.

I led development on the Princeton MVPA toolbox for Matlab, an open source package to facilitate these kinds of analyses.

Pittsburgh EBC fMRI analysis competition

Similarity structure and spatial working memory

As part of my master’s thesis, I worked (with Ken Norman) on a novel multivariate method for exploratory fMRI analysis. It calculates the isomorphism between the pattern of activity in a brain region and the patterns predicted by rich psychological models. In my thesis, I show that we can better predict which location someone is covertly attending to with this multivariate ‘similarity structure’ method than with standard or univariate measures on a spatial working memory dataset. I also attempt to relate this to my work on temporal context and memory.